A lightweight SHADE-based algorithm for global optimization - liteSHADE

Viktorin, Adam; Šenkeřík, Roman; Pluháček, Michal; Kadavý, Tomáš; Jašek, Roman

dc.title	A lightweight SHADE-based algorithm for global optimization - liteSHADE	en
dc.contributor.author	Viktorin, Adam
dc.contributor.author	Šenkeřík, Roman
dc.contributor.author	Pluháček, Michal
dc.contributor.author	Kadavý, Tomáš
dc.contributor.author	Jašek, Roman
dc.relation.ispartof	Lecture Notes in Electrical Engineering
dc.identifier.issn	1876-1100 Scopus Sources, Sherpa/RoMEO, JCR
dc.identifier.isbn	978-3-03-014906-2
dc.date.issued	2020
utb.relation.volume	554
dc.citation.spage	197
dc.citation.epage	206
dc.event.title	5th International Conference on Advanced Engineering Theory and Applications, AETA 2018
dc.event.location	Ostrava
utb.event.state-en	Czech Republic
utb.event.state-cs	Česká republika
dc.event.sdate	2018-09-11
dc.event.edate	2018-09-13
dc.type	conferenceObject
dc.language.iso	en
dc.publisher	Springer Verlag
dc.identifier.doi	10.1007/978-3-030-14907-9_20
dc.relation.uri	https://link.springer.com/chapter/10.1007/978-3-030-14907-9_20
dc.subject	Differential Evolution	en
dc.subject	liteSHADE	en
dc.subject	SHADE	en
dc.subject	Simplification	en
dc.description.abstract	In this paper, a novel lightweight version of the Successful-History based Adaptive Differential Evolution (SHADE) is presented as the first step towards a simple, user-friendly, metaheuristic algorithm for global optimization. This simplified algorithm is called liteSHADE and is compared to the original SHADE on the CEC2015 benchmark set in three dimensional settings – 10D, 30D and 50D. The results support the idea, that simplification may lead to a successful and understandable algorithm with competitive or even better performance. © Springer Nature Switzerland AG 2020.	en
utb.faculty	Faculty of Applied Informatics
dc.identifier.uri	http://hdl.handle.net/10563/1008756
utb.identifier.obdid	43881237
utb.identifier.scopus	2-s2.0-85066338041
utb.source	d-scopus
dc.date.accessioned	2019-08-13T10:17:18Z
dc.date.available	2019-08-13T10:17:18Z
utb.ou	CEBIA-Tech
utb.contributor.internalauthor	Viktorin, Adam
utb.contributor.internalauthor	Šenkeřík, Roman
utb.contributor.internalauthor	Pluháček, Michal
utb.contributor.internalauthor	Kadavý, Tomáš
utb.contributor.internalauthor	Jašek, Roman
utb.fulltext.affiliation	Adam Viktorin, Roman Senkerik, Michal Pluhacek, Tomas Kadavy, Roman Jasek Faculty of Applied Informatics, Tomas Bata University in Zlin, T. G. Masaryka 5555, 760 01 Zlin, Czech Republic {aviktorin,senkerik,pluhacek,kadavy,jasek}@utb.cz
utb.fulltext.dates	-
utb.fulltext.sponsorship	This work was supported by the Ministry of Education, Youth and Sports of the Czech Republic within the National Sustainability Programme Project no. LO1303 (MSMT-7778/2014), further by the European Regional Development Fund under the Project CEBIA-Tech no. CZ.1.05/2.1.00/03.0089 and by Internal Grant Agency of Tomas Bata University under the Projects no. IGA/CebiaTech/2019/002. This work is also based upon support by COST (European Cooperation in Science & Technology) under Action CA15140, Improving Applicability of Nature-Inspired Optimisation by Joining Theory and Practice (ImAppNIO), and Action IC1406, High-Performance Modelling and Simulation for Big Data Applications (cHiPSet). The work was further supported by resources of A.I.Lab at the Faculty of Applied Informatics, Tomas Bata University in Zlin (ailab.fai.utb.cz).
utb.scopus.affiliation	Faculty of Applied Informatics, Tomas Bata University in Zlin, T. G. Masaryka 5555, Zlin, 760 01, Czech Republic
utb.fulltext.projects	LO1303
utb.fulltext.projects	CZ.1.05/2.1.00/03.0089
utb.fulltext.projects	IGA/CebiaTech/2019/002
utb.fulltext.projects	CA15140
utb.fulltext.faculty	Faculty of Applied Informatics
utb.fulltext.faculty	Faculty of Applied Informatics
utb.fulltext.faculty	Faculty of Applied Informatics
utb.fulltext.faculty	Faculty of Applied Informatics
utb.fulltext.faculty	Faculty of Applied Informatics